Travailler sur le pipeline de données, du train au cloud, incluant l'installation et le développement de l'infrastructure informatique à bord des trains, ainsi que l'analyse et la visualisation des données, dans le but de maintenir la plateforme de maintenance prédictive d'Alstom basée sur les données pour le nouveau projet REM. Participer à des réunions quotidiennes en français et en anglais.

Worked on various stages of the train to cloud data pipeline, from configuration of on-train computer networks to data analysis and visualization in support of Alstom's data-driven predictive maintenance platform, on the new REM line. Daily meetings in French and English.

Brainstorm ideas for articles, conducts interviews with sources, and write articles for weekly publications.

Researched and designed deep learning algorithms and computer graphics for facial recognition in driver monitoring systems in Toyota’s autonomous vehicles.

Liaised between Japanese-speaking teams and English-speaking teams to arrange collaborations

Initiated research in ray tracing (physics-based computer graphics), supervised and funded by McGill Mathematics Department.

Used numerical analysis to evaluate validity of geometric and numerical-algorithmic solutions. Wrote ray tracer in C from scratch to render images using developed techniques.

Objective of the project is to optimize ray tracing to compute color data for each pixel in one (constant-time) calculation, by creating generalized signed distance functions (SDF) for individual shapes. This has been successfully done for many shapes, while preserving the useful properties of existing SDF theory. When generalized SDF were not viable, numerical solutions which proved to run with adequate speed (linear time with respect to the number of pixels) were developed, deployed, and proved usable.